空间机器人捕获航天器后基于无源性理论的鲁棒镇定控制

研究了漂浮基空间机器人捕获非合作航天器过程对系统产生的冲击效应及其后联合体系统镇定运动的控制问题。为此,利用拉格朗日方法及牛顿-欧拉法分别获得了捕获前空间机器人及目标航天器的动力学模型;结合动量守恒定律、系统运动几何关系及力的传递规律,分析了捕获过程相互碰撞所产生的冲击效应,建立了捕获完成后两者联合体的系统动力学模型。在此基础上,针对同时存在不确定参数及外部扰动的联合体系统,设计了基于无源性理论的镇定运动神经网络H_∞鲁棒控制算法。本文提出的基于无源性理论设计的鲁棒控制算法具有良好的动态特性及较强的鲁棒性,可快速完成系统的镇定控制,实现轨迹的精确跟踪。系统数值模拟仿真验证了本文控制方案的正确性。     

带形域内裂纹对SH波散射问题的边界元解

采用边界元法研究含裂纹的带形域各向同性弹性体，裂纹对SH波的散射问题，推导出带形域情况下不同边界条件的各种Green函数，导出了以裂纹张开位移为未知数的边界积分方程，计算出表面散射场和总位移．算例表明，利用所提供的格林函数和边界元格式解答带形域的散射问题比较方便．     

紧黎曼面上一类线丛截面空间的基

对于亏格g≥1的紧Riemann曲面M,本文运用Riemann-Roch定理,证明了其上线丛Lλ(M)的某类截面空间非空集,并利用Theta函数和素形式构造出这类截面空间的一组基．     

基于自适应径向基神经网络的类星体光谱自动识别方法

通过对光谱的研究来识别和认证类星体是天文学研究中的重要方法。文章提出了一种对类星体光谱进行自动识别的自适应径向基神经网络(RBFN)方法。该方法包括以下几个步骤: (1)先将训练样本归一化,再利用PCA变换进行降维,获得样本特征向量; (2)设计出K均值聚类算法与梯度下降法相结合的径向基神经网络结构的基本模型,再用SSE(sum of squares error)误差函数进行判断,对RBFN隐含层的神经元进行自动调节,直至满足给定误差阈值; (3)用训练得到的参数对用于测试的样本中的类星体光谱进行识别。该方法不但克服了经典RBFN算法选择隐层神经元数目的困难,而且还提高了对类星体识别的稳定性和正确率。研究结果对于大型光谱巡天所产生的海量数据的自动处理具有重要意义。     

STABLE SOLUTION OF TIME DOMAIN INTEGRAL EQUATION METHODS USING QUADRATIC B-SPLINE TEMPORAL BASIS FUNCTIONS

This paper is concerned with stable solutions of time domain integral equation （TDIE） methods for transient scattering problems with 3D conducting objects. We use the quadratic B-spline function as temporal basis functions, which permits both the induced currents and induced charges to be properly approximated in terms of completeness. Because the B-spline function has the least support width among all polynomial basis functions of the same order, the resulting system matrices seem to be the sparsest. The TDIE formula-tions using induced electric polarizations as unknown function are adopted and justified. Numerical results demonstrate that the proposed approach is accurate and efficient, and no late-time instability is observed.     

Structure of ^6He in the frame of a cluster model

A microscopic cluster model with a fully correlated Gaussian basis is developed. In the model, the stochastic variational method is used in order to calculate the ground-energy and the mean-square radius conveniently. Based on this model, the ground-energy level and radius of the neutron halo nucleus, ⁶He, are calculated as a α+n+n three-cluster model. The results are in good agreement with the experimental data.     

An eigen-based high-order expansion basis for structured spectral elements

We present an eigen-based high-order expansion basis for the spectral element approach with structured elements. The new basis exhibits a numerical efficiency significantly superior, in terms of the conditioning of coefficient matrices and the number of iterations to convergence for the conjugate gradient solver, to the commonly-used Jacobi polynomial-based expansion basis. This basis results in extremely sparse mass matrices, and it is very amenable to the diagonal preconditioning. Ample numerical experiments demonstrate that with the new basis and a simple diagonal preconditioner the number of conjugate gradient iterations to convergence has essentially no dependence or only a very weak dependence on the element order. The expansion bases are constructed by a tensor product of a set of special one-dimensional (1D) basis functions. The 1D interior modes are constructed such that the interior mass and stiffness matrices are simultaneously diagonal and have identical condition numbers. The 1D vertex modes are constructed to be orthogonal to all the interior modes. The performance of the new basis has been investigated and compared with other expansion bases.     

OBE理念推动化工设备机械基础课程的改革实践*

以应用型人才培养为目标,探索了利用OBE理念推动化工设备机械基础课程及其课程设计的改革实践。以OBE理念为指导,结合CDIO和LBL的教学模式,提出在教学内容、平台在线课程建设、第二课堂教学、课程设计和考核方法等方面的改革方案,增强了课程的应用性和成果产出,不仅提高了学生对理论知识掌握的牢固度,更提高了学生的实践能力、对知识的灵活应用能力和创新能力,与实际应用连接更加紧密,有效地实现了高素质的应用型人才输出。     

Evolutionary Pareto distributions

We consider here i.i.d. variables which are distributed according to a Pareto up to some point x₁ and a Pareto (with a different parameter) after this point. This model constitutes an approximation for estimating extreme tail probabilities, especially for financial or insurance data. We estimate the parameters by maximizing the likelihood of the sample, and investigate the rates of convergence and the asymptotic laws. We find here a problem which is very close to the change point question from the point of view of limits of experiments. Especially, the rates of convergence and the limiting law obtained here are the same as in a change point framework. Simulations are giving an illustration of the quality of the procedure.